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chatgenius-mcp

chatgenius-mcp

Official
by SumCodeAI

get_competitor_leaderboard

Read-onlyIdempotent

Compare your Instagram account with competitors in one ranked table: followers, engagement rate, posting frequency, average likes/comments, daily follower growth, and content mix for 7, 30, or 90 days.

Instructions

Get the leaderboard. Your account and every competitor ranked together: followers, engagement rate, posts per week, average likes and comments, follower growth per day and the content mix (reels, photos, carousels). This is the table behind the portal's Market Intel page. Stored snapshots, so it is instant and spends no Meta quota. Your account and every competitor ranked together. Start here for any "how do I compare" question.

Input Schema

NameRequiredDescriptionDefault
periodNoWindow in days. Default 30.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the bar is lower; the description still adds real value by disclosing that results come from stored snapshots, are instant, and consume no Meta quota. It doesn't say how stale the snapshot may be or that refresh_market_intel exists to update it, which is the one behavioral gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Metrics are front-loaded and the quota/snapshot note earns its place, but "Your account and every competitor ranked together" is repeated verbatim in two separate sentences, which is unambiguous waste. The "table behind the portal's Market Intel page" line is useful orientation but adds length to an already-redundant paragraph.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read tool with full annotation coverage and no output schema, the description supplies what the schema cannot: what fields the ranking actually contains. Only the snapshot freshness/refresh path is unaddressed, which is minor for a cached read.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single enum parameter already documents the 7/30/90 window and default of 30. The description adds no syntax, default, or interpretation detail beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and enumerates exactly what is ranked: followers, engagement rate, posts per week, average likes/comments, follower growth per day, and content mix. It also disambiguates from neighbors like get_competitor and get_wins_and_opportunities by framing the tool as the combined account-vs-competitor comparison table.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Start here for any 'how do I compare' question" gives explicit entry-point guidance for a whole class of queries. It stops short of naming an alternative (e.g. get_wins_and_opportunities for the diagnostic follow-up, refresh_market_intel for fresher data), so the when-not-to-use case is left implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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